Bibliographic record
Abstract
PURPOSE OF REVIEW: The purpose of this review is to highlight the demand for fertility preservation among cancer survivors and to draw attention to areas where healthcare workers need to improve. As technology advances, maximizing cryopreservation rates will be paramount to increase the ability individuals to conceive after cancer treatment. RECENT FINDINGS: Guidelines recommending discussion of fertility for those diagnosed with cancer have been shown to increase patient satisfaction and overall quality of life. Our review demonstrated that increasing counseling rates remains an ongoing challenge and should remain an area of improvement for all healthcare professionals working in the oncology field. Formal programs to improve patient and provider education and access to fertility preservation increase uptake of fertility preservation. For men, many options exist to cryopreserve sperm; a slight delay to achieve fertility preservation has not been shown to lead to worse outcomes. Cryopreservation strategies differ based on puberty status and remain an active area of clinical research. SUMMARY: Improving fertility outcomes for cancer survivors is possible with appropriate counseling techniques at the time of cancer diagnosis. Clinicians should challenge current barriers for patient access to fertility preservation surrounding cancer treatments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".